{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载模块"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "import pylab as pl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 简单线形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1, 2, 3, 10])\n",
    "plt.xlabel(\"x-axis\")\n",
    "plt.ylabel(\"my numbers\")\n",
    "plt.title(\"my figuer\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 曲线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(-np.pi, np.pi, 256, endpoint = True)\n",
    "C,S = np.cos(x),np.sin(x)\n",
    "pl.plot(x, C), pl.plot(x, S)\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 关系散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n= 1024\n",
    "X = np.random.normal(0, 1, n)\n",
    "Y = np.random.normal(0, 1, n)\n",
    "pl.scatter(X, Y)\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 单利和复利曲线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pv = 1000\n",
    "r = 0.08\n",
    "n = 10\n",
    "t = pl.linspace(0, n, n)\n",
    "y1 = np.ones(len(t)) * pv #this is a horizontal line\n",
    "y2 = pv * (1 + r * t)\n",
    "y3 = pv * (1 + r) ** t\n",
    "pl.title('Simple vs. Compounded interest rates')\n",
    "pl.xlabel('number of years')\n",
    "pl.ylabel('Values')\n",
    "pl.xlim(0, 11)\n",
    "pl.ylim(800, 2000)\n",
    "pl.plot(t, y1, 'b-')\n",
    "pl.plot(t, y2, 'g--')\n",
    "pl.plot(t, y3, 'r-')\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 线形图标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x4 = [0, 1, 2]\n",
    "y4 = [2, 4, 6]\n",
    "pl.plot(x4, y4)\n",
    "pl.figtext(0.2, 0.7, 'North & West')\n",
    "pl.figtext(0.7, 0.2, 'South & East')\n",
    "pl.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 财务比率柱形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ind = np.arange(3)\n",
    "plt.title('DuPont Identity')\n",
    "plt.xlabel('Different companies')\n",
    "plt.ylabel('Three Ratios')\n",
    "ROE = [0.88, 0.22, 0.22]\n",
    "a = [0.16, 0.04, 0.036]\n",
    "b = [0.88, 1.12, 2.31]\n",
    "c = [6.32, 4.45, 2.66]\n",
    "width = 0.45\n",
    "plt.figtext(0.2, 0.85, 'ROE = 0.88')\n",
    "plt.figtext(0.5, 0.7, 'ROE = 0.22')\n",
    "plt.figtext(0.8, 0.6, 'ROE = 0.22')\n",
    "plt.figtext(0.2, 0.75, 'Profit Margin = 0.16')\n",
    "plt.figtext(0.5, 0.5, '0.041')\n",
    "plt.figtext(0.8, 0.4, '0.036')\n",
    "p1 = plt.bar(ind, a, width, color = 'b')\n",
    "p2 = plt.bar(ind, b, width, color = 'r', bottom = a)\n",
    "index_a = range(2)\n",
    "for j in index_a: \n",
    "    bottom_aAndb = a[j] + b[j] \n",
    "    p3: object = plt.bar(ind, c, width, color = 'y', bottom = bottom_aAndb)\n",
    "plt.xticks(ind + width / 2., ('IBM', 'DELL', 'WMT'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NPV曲线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cashflows = [-100, 50, 60, 70]\n",
    "rate = []\n",
    "npv = []\n",
    "x = (0, 0.7)\n",
    "y = (0, 0)\n",
    "for i in range(1, 70):\n",
    "    rate.append(0.01 * i)\n",
    "    npv.append(sp.npv(0.01 * i, cashflows))\n",
    "plt.plot(rate, npv), plt.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 多个IRR曲线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.08949087038126313"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cashflows = [504, -432, -432, -432, 832]\n",
    "rate = []\n",
    "npv = []\n",
    "x = (0, 0.3)\n",
    "y = (0, 0)\n",
    "for i in range(1, 30):\n",
    "    rate.append(0.01 * i)\n",
    "    npv.append(sp.npv(0.01 * i, cashflows))\n",
    "plt.plot(rate, npv), plt.plot(x, y)\n",
    "plt.show()\n",
    "np.irr(cashflows)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 股票每股收益柱形图标注线段"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "A_ESP = (5.02, 4.54, 4.18, 3.73)\n",
    "B_ESP = (1.35, 1.88, 1.35, 0.73)\n",
    "ind = np.arange(len(A_ESP)) # the x locations for the groups\n",
    "width = 0.4 # the width of the bars\n",
    "fig, ax = plt.subplots()\n",
    "A_std = B_std = (2, 2, 2, 2)\n",
    "rects1 = ax.bar(ind, A_ESP, width, color = 'r', yerr = A_std)\n",
    "rects2 = ax.bar(ind + width, B_ESP, width, color = 'y', yerr = A_std)\n",
    "ax.set_ylabel('EPS')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Diluted EPS Excluding Extraordinary Items')\n",
    "ax.set_xticks(ind + width)\n",
    "ax.set_xticklabels(('2012', '2011', '2010', '2009'))\n",
    "ax.legend((rects1[0], rects2[0]), ('W-mart', 'Dell'))\n",
    "def autolabel(rects):\n",
    "    for rect in rects:\n",
    "        height = rect.get_height()\n",
    "        ax.text(rect.get_x() + rect.get_width() / 2., 1.05 * height, '%d'%int(height), ha = 'center', va = 'bottom')\n",
    "autolabel(rects1)\n",
    "autolabel(rects2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 股票收益线形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.109 0.146 0.127\n",
      "0.075 0.074 0.027\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[ 1.        , -0.74583429],\n",
       "       [-0.74583429,  1.        ]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year = [2009, 2010, 2011, 2012, 2013]\n",
    "ret_A = [0.102, -0.02, 0.213, 0.12, 0.13]\n",
    "ret_B = [0.1062, 0.23, 0.045, 0.234, 0.113]\n",
    "port_EW = (np.array(ret_A) + np.array(ret_B)) / 2.\n",
    "print(round(np.mean(ret_A), 3), round(np.mean(ret_B), 3), round(np.mean(port_EW), 3))\n",
    "print(round(np.std(ret_A), 3), round(np.std(ret_B), 3), round(np.std(port_EW), 3))\n",
    "plt.figtext(0.2, 0.65, \"Stock A\")\n",
    "plt.figtext(0.15, 0.4, \"Stock B\")\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Returns\")\n",
    "plt.plot(year, ret_A, lw = 2)\n",
    "plt.plot(year, ret_B, lw = 2)\n",
    "plt.plot(year, port_EW, lw = 2)\n",
    "plt.title(\"Individual stocks vs. an equal-weighted 2-stock portfolio\")\n",
    "plt.annotate(\"Equal-weighted Portfolio\", xy = (2010, 0.1), xytext = (2011, 0), arrowprops = dict(facecolor = 'black', shrink = 0.05))\n",
    "plt.ylim(-0.1, 0.3)\n",
    "plt.show()\n",
    "sp.corrcoef(ret_A, ret_B)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 投资组合风险曲线图标注"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n= [1, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 25, 30, 35, 40, 45, 50]\n",
    "port_sigma = [0.49236, 0.37358, 0.29687, 0.26643, 0.24983, 0.23932, 0.23204, 0.22670, 0.22261, 0.21939, 0.21677, 0.21196, 0.2087, 0.20634, 0.20456, 0.20316, 0.20203]\n",
    "plt.xlim(0, 50)\n",
    "plt.ylim(0.1, 0.4)\n",
    "plt.hlines(0.19217, 0, 50, colors = 'r', linestyles = 'dashed')\n",
    "plt.annotate('', xy = (5, 0.19), xycoords = 'data', xytext = (5, 0.28), textcoords = 'data', arrowprops = {'arrowstyle':'<->'})\n",
    "plt.annotate('', xy = (30, 0.19), xycoords = 'data', xytext = (30, 0.1), textcoords = 'data', arrowprops = {'arrowstyle':'<->'})\n",
    "plt.annotate('Total portfolio risk', xy = (5, 0.3), xytext = (25, 0.35), arrowprops = dict(facecolor = 'black', shrink = 0.02))\n",
    "plt.figtext(0.15, 0.4, \"Diversiable Risk\")\n",
    "plt.figtext(0.65, 0.25, \"Nondiversiable Risk\")\n",
    "plt.plot(n[0:17], port_sigma[0:17])\n",
    "plt.title(\"Relationship between n and portfolio risk\")\n",
    "plt.xlabel(\"Number of stocks in a portfolio\")\n",
    "plt.ylabel(\"Ratio of Portfolio std to std of one stock\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 收集Yahoo财经股票数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tushare as tus\n",
    "date1 = (2012, 1, 1)\n",
    "date2 = (2012, 12, 31)\n",
    "price = tus.get_hist_data(code = \"IBM\", start = date1, end = date2, ktype = 'D')\n",
    "import datetime\n",
    "import matplotlib.mlab as mlab\n",
    "ticker = \"IBM\"\n",
    "begdate = datetime.date(2013, 1, 1)\n",
    "enddate = datetime.date.today()\n",
    "price2 = tus.get_hist_data(code = ticker, start = begdate, end = enddate, ktype = 'D')\n",
    "#r = mlab.csv2rec(price2); price2.close()\n",
    "#r.sort()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function csv2rec in module matplotlib.mlab:\n",
      "\n",
      "csv2rec(fname, comments='#', skiprows=0, checkrows=0, delimiter=',', converterd=None, names=None, missing='', missingd=None, use_mrecords=False, dayfirst=False, yearfirst=False)\n",
      "    .. deprecated:: 2.2\n",
      "        The csv2rec function was deprecated in Matplotlib 2.2 and will be removed in 3.1.\n",
      "    \n",
      "    Load data from comma/space/tab delimited file in *fname* into a\n",
      "    numpy record array and return the record array.\n",
      "    \n",
      "    If *names* is *None*, a header row is required to automatically\n",
      "    assign the recarray names.  The headers will be lower cased,\n",
      "    spaces will be converted to underscores, and illegal attribute\n",
      "    name characters removed.  If *names* is not *None*, it is a\n",
      "    sequence of names to use for the column names.  In this case, it\n",
      "    is assumed there is no header row.\n",
      "    \n",
      "    \n",
      "    - *fname*: can be a filename or a file handle.  Support for gzipped\n",
      "      files is automatic, if the filename ends in '.gz'\n",
      "    \n",
      "    - *comments*: the character used to indicate the start of a comment\n",
      "      in the file, or *None* to switch off the removal of comments\n",
      "    \n",
      "    - *skiprows*: is the number of rows from the top to skip\n",
      "    \n",
      "    - *checkrows*: is the number of rows to check to validate the column\n",
      "      data type.  When set to zero all rows are validated.\n",
      "    \n",
      "    - *converterd*: if not *None*, is a dictionary mapping column number or\n",
      "      munged column name to a converter function.\n",
      "    \n",
      "    - *names*: if not None, is a list of header names.  In this case, no\n",
      "      header will be read from the file\n",
      "    \n",
      "    - *missingd* is a dictionary mapping munged column names to field values\n",
      "      which signify that the field does not contain actual data and should\n",
      "      be masked, e.g., '0000-00-00' or 'unused'\n",
      "    \n",
      "    - *missing*: a string whose value signals a missing field regardless of\n",
      "      the column it appears in\n",
      "    \n",
      "    - *use_mrecords*: if True, return an mrecords.fromrecords record array if\n",
      "      any of the data are missing\n",
      "    \n",
      "    - *dayfirst*: default is False so that MM-DD-YY has precedence over\n",
      "      DD-MM-YY.  See\n",
      "      http://labix.org/python-dateutil#head-b95ce2094d189a89f80f5ae52a05b4ab7b41af47\n",
      "      for further information.\n",
      "    \n",
      "    - *yearfirst*: default is False so that MM-DD-YY has precedence over\n",
      "      YY-MM-DD. See\n",
      "      http://labix.org/python-dateutil#head-b95ce2094d189a89f80f5ae52a05b4ab7b41af47\n",
      "      for further information.\n",
      "    \n",
      "      If no rows are found, *None* is returned\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "help(mlab.csv2rec)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算年化收益率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.22307467049722787\n"
     ]
    }
   ],
   "source": [
    "from scipy import stats\n",
    "pc_array = [1.01, 1.05, 0.99, 1.02, 0.99]\n",
    "annual_return = (stats.gmean(pc_array)-1)*(360**0.5)\n",
    "print(annual_return)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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